%0 Computer Program %A Spierenburg, Lucas %D 2022 %T Code for the paper "Characterizing residential segregation in cities using intensity, separation, and scale indicators" %U https://data.4tu.nl/articles/software/Code_for_the_paper_Characterizing_residential_segregation_in_cities_using_intensity_separation_and_scale_indicators_/21286653/1 %R 10.4121/21286653.v1 %K software %X

This code is used for computing the results of the paper "Characterizing residential segregation in cities using intensity, separation, and scale indicators". 


This code identifies and characterizes residential segregation patterns from demographic data. It is applied in a Dutch case study. It is written in python, using notebooks.


This source code should be stored in a folder named code. The folder code and the folder data (see https://doi.org/10.4121/19597258) should be located in the same directory.

FORMAT

*.mkd;

*.ipynb;

*.txt;

*.csv

RECOMMENDED HARDWARE

1. Processor: Intel® Core™ i5-10210U CPU

2. RAM: 32GiB of RAM (DDR4)

3. GPU: Intel® UHD Graphics GPU

RECOMMENDED OPERATING SYSTEM

Ubuntu 21.10, 64-bit

REQUIRED VERSION OF PYTHON

3.9.7

REQUIRED LIBRARIES USED

see requirements.txt

EXTRA FILE

parameter.csv specifies some parameters used in the analysis.

SEQUENCE OF SCRIPTS

The scripts should be run in the following order:


1. demographics_preprocess.ipynb

2. extract_city_boundary.ipynb

3. extract_street_network.ipynb

4. extract_zones_in_gemeente.ipynb

5. shortest_path.ipynb

6. adjacency_matrix.ipynb

7. correlation_matrix.ipynb

8. exposure.ipynb

9. cluster_analysis.ipynb

10. descriptive_stats.ipynb

11. combine_zones_into_municipalities.ipynb

%I 4TU.ResearchData